containerization , Machine Learning, Orchestration, Tensorflow, MLops, Pytorch, DevSecOps, Databricks, Python, AWS, Scikit-learn, Distributed Data Processing

Pyspark, Tensorflow, Numpy, Git, Pandas, Pytorch, XGBoost, Keras, Python, scikit-learn, LightGBM, TensorFlow Serving, TensorRT, MLflow, ONNX, Azure ML Pipelines, Kubeflow, TorchServe, CatBoost

Pyspark, Tensorflow, Numpy, Git, Pandas, Pytorch, XGBoost, Keras, Python, scikit-learn, LightGBM, TensorFlow Serving, TensorRT, MLflow, ONNX, Azure ML Pipelines, Kubeflow, TorchServe, CatBoost

Azure ML, Azure Data Factory, Databricks, Python, CrewAI, agentic AI frameworks, orchestration tools, AI governance frameworks, Clean Architecture, model generalization techniques, static analysis tools, Semantic Kernel, AutoGen, LangGraph, ML engineering, ETL workflows

Sql, MLops, Terraform, Arm, Azure Machine Learning, Python, ServiceNow AI ML Predictive Intelligence, Microsoft Azure AI, Infrastructure as Code, Virtual Agent, Azure OpenAI, API-based integrations, Kore.ai XO Platform, CI CD pipelines, Bicep

3d reconstruction , object detection , Mvs, Tensorflow, Numpy, Opencv, Pytorch, Python, SLAM, COLMAP, semantic instance segmentation, SfM, 3D vision techniques

Machine Learning, Gcp, Data Modeling, Algorithm Development, Azure, Python, AWS, R, analytics tools, cloud-based ML platforms, large datasets

Java, Python, Scala, Deployment practices, ML lifecycle